Lyrics Generation Guide
This guide explains how to use the fine-tuned GPT-Neo 2.7B model to generate lyrics in different styles and themes.
Basic Usage
The basic command to generate lyrics is:
python generate_lyrics_english.py --artist "Artist Name" --use_cpu
This will generate lyrics in the style of the specified artist.
Available Parameters
The script supports the following parameters:
| Parameter | Description | Default |
|---|---|---|
--artist |
The artist name to emulate | "Taylor Swift" |
--theme |
Theme or topic for the lyrics | "" (none) |
--style |
Style of the lyrics (e.g., romantic, upbeat, sad) | "" (none) |
--prompt |
Custom text to start the lyrics | "" (none) |
--max_length |
Maximum length of generated text | 200 |
--temperature |
Generation temperature (higher = more diverse) | 0.7 |
--top_p |
Nucleus sampling probability threshold | 0.9 |
--num_samples |
Number of samples to generate | 1 |
--use_cpu |
Use CPU for inference | False |
--model_path |
Path to the model | Final model path |
--checkpoint_path |
Path to a specific checkpoint | Checkpoint-900 |
Example Prompts
1. Basic Artist Emulation
python generate_lyrics_english.py --artist "Taylor Swift" --use_cpu
2. Artist with Theme
python generate_lyrics_english.py --artist "Beyonce" --theme "empowerment" --use_cpu
3. Artist with Style
python generate_lyrics_english.py --artist "Ed Sheeran" --style "romantic" --use_cpu
4. Artist with Theme and Style
python generate_lyrics_english.py --artist "Adele" --theme "heartbreak" --style "emotional" --use_cpu
5. Artist with Custom Starting Prompt
python generate_lyrics_english.py --artist "Bruno Mars" --prompt "Dancing in the moonlight" --use_cpu
6. Complete Specification
python generate_lyrics_english.py --artist "Lady Gaga" --theme "freedom" --style "upbeat" --prompt "I was born this way" --use_cpu
Controlling Generation Parameters
Temperature
The temperature parameter controls the randomness of the generation. Higher values (e.g., 1.0) make the output more diverse but potentially less coherent, while lower values (e.g., 0.5) make the output more focused and deterministic.
# More creative output
python generate_lyrics_english.py --artist "Ariana Grande" --temperature 1.0 --use_cpu
# More focused output
python generate_lyrics_english.py --artist "Drake" --temperature 0.5 --use_cpu
Top-p (Nucleus Sampling)
The top-p parameter controls the diversity of the generation by considering only the most probable tokens whose cumulative probability exceeds the threshold.
# More diverse output
python generate_lyrics_english.py --artist "Beyonce" --top_p 0.95 --use_cpu
# More focused output
python generate_lyrics_english.py --artist "Beyonce" --top_p 0.7 --use_cpu
Maximum Length
Control the length of the generated lyrics:
# Shorter lyrics
python generate_lyrics_english.py --artist "Taylor Swift" --max_length 100 --use_cpu
# Longer lyrics
python generate_lyrics_english.py --artist "Taylor Swift" --max_length 300 --use_cpu
Batch Generation
Generate multiple samples at once:
python generate_lyrics_english.py --artist "Taylor Swift" --num_samples 5 --use_cpu
Tips for Better Results
Be specific with artists: The model was trained on specific artists' styles, so using those artists will yield better results.
Combine parameters: Using a combination of theme, style, and prompt often yields the most interesting and coherent results.
Experiment with temperature: If the output is too repetitive, try increasing the temperature. If it's too random, try decreasing it.
Use CPU mode for reliability: While GPU mode is faster, CPU mode is more reliable for avoiding memory issues.
Try different starting prompts: The starting prompt can significantly influence the direction of the generated lyrics.
Running the Examples Script
For a quick demonstration of different prompt combinations, run:
./english_prompt_examples.sh
This will run through several example prompts with different configurations.